User: rproendo

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rproendo0
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Posts by rproendo

<prev • 14 results • page 1 of 2 • next >
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Comment: C: Implications of TMM Normalization and Possible Alternatives
... Okay, thank you for the advice, Gordon. I'll try your suggestions! ...
written 23 days ago by rproendo0
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Comment: C: Implications of TMM Normalization and Possible Alternatives
... Alright, thank you for the feedback Aaron! I'll switch over to QL methods, as well. Happy holidays. ...
written 25 days ago by rproendo0
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Implications of TMM Normalization and Possible Alternatives
... Hi all, I'm relying on edgeR for differential expression analysis and have thus far been using TMM normalization to account for library composition effects, but I'm finding a very large number of DEGs. In this case, I'm unsure if my data set violates any assumptions for TMM, how robust TMM might be ...
normalization edger deg tmm written 26 days ago by rproendo0 • updated 24 days ago by Gordon Smyth36k
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Comment: C: Filtering, minimum sample number, and condition in edgeR
... Hi, Ryan Thanks for your quick response! I'll have to figure out a way to rapidly check if a single library is contributing (other than a PCA or plotMDS), but will look into this immediately. I'll also try the limma method. In terms of library quality, upstream QA analysis with FastQC didn't throw ...
written 7 weeks ago by rproendo0
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Comment: C: Filtering, minimum sample number, and condition in edgeR
... Hi, James Thanks for the quick response. I will look into filterByExpr immediately. And I understand the distinction, and I'll have to look into some means to address how many DEGs are coming back post-filtering that might be due to one very high sample.  In fact, the inspiration for the post was ...
written 7 weeks ago by rproendo0
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Filtering, minimum sample number, and condition in edgeR
... Hi all, I'm using edgeR for DEG analysis and have run into a snag with my filtering approach. I have an experimental design wherein individuals from two different populations were treated with a drug or left untreated. This is not a repeated measures, and replicates are not shared between treated a ...
edger filtering written 7 weeks ago by rproendo0 • updated 7 weeks ago by Ryan C. Thompson7.1k
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Comment: C: Differentiating between batch and treatment effects in edgeR, DESeq2
... Got it! Thanks again, Aaron. Yes -- we would go all the way back to RNA, generating new libraries, and sequencing new libraries de novo for C.N, C.T, B.N, and B.T. Thank you! ...
written 11 weeks ago by rproendo0
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Comment: C: Differentiating between batch and treatment effects in edgeR, DESeq2
... Okay, I follow. Sorry for the confusion and thank you for weighing in. I go into additional detail below in response to Aaron, but we have Treated and Control for all three populations. We have thus far sequenced A and B treated and control, and are considering sequencing C treated and control. But ...
written 12 weeks ago by rproendo0
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Comment: C: Differentiating between batch and treatment effects in edgeR, DESeq2
... Ahh, okay. I follow -- thank you, Aaron (and James) for clarifying. I have framed the question up to this point as wanting to compare responses between population (C.T - C.N) versus (A.T - A.N), but we DO also care about comparing C.N to A.N and B.N. I assumed specifying all of the questions I wante ...
written 12 weeks ago by rproendo0
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Comment: C: Differentiating between batch and treatment effects in edgeR, DESeq2
... Hi, James. The distinction between the example in section 3.5 is that our samples within populations are not paired by subject. Thus, we are not comparing responses pre- and post-treatment in a repeated measures design for any of the populations. Nonetheless, the approach to specifying contrasts out ...
written 12 weeks ago by rproendo0

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